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How to Use Reaxys Reaction Data to Create Chemistry Models

Posted on February 11th, 2021 by

These days, a chemist’s digital tools are as valued as the physical ones, and those digital tools are enabling chemists to do some amazing things in the lab. One example is predictive reaction chemistry, a thriving area with a rapidly-developing variety of algorithms and approaches.   

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The 10th Anniversary Reaxys PhD Prize Symposium: A Virtual Success

Posted on December 21st, 2020 by

No one anticipated that the 10th anniversary Reaxys PhD Prize Symposium would be a virtual event, but as we discussed earlier on in this blog, most gatherings of scientific researchers have had to go online this year because of COVID-19. As it turned out, the virtual symposium was a very special event in its own right.

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Interview with Greg Landrum at Elsevier: What are the ingredients of a successful Open Source cheminformatics software?

Posted on November 30th, 2020 by

(Written by Elena Herzog in collaboration with Markus Fischer, Gerd Blanke, Jarek Tomczac and Gabrielle Whittick)

RDKit, a collection of cheminformatics and machine learning software, is assisting in solving chemical information challenges. The founder and creator of RDKit, Greg Landrum, was interviewed by the UDM (Unified Data Model) team, facilitated by Elsevier, to share his experience on what the road to success looks like and what ingredients does an open source project need to have to be successful. The learnings from the interview would help to shape the future of the UDM project, which is transferring from its consortium-led Pistoia Alliance model to a community-led model.

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Bringing Scalability Into Chemistry Modeling

Posted on November 18th, 2020 by

Synthetic chemistry has been with us for centuries, but it is now entering a new frontier. Big data, AI and machine learning are unlocking a predictive power that is transforming the conceptualization and optimization of synthetic routes.

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